Brain Computer Interface Control of a Virtual Robotic based on SSVEP and EEG Signal By: Fatemeh Akrami Supervisor: Dr. Hamid D. Taghirad October 2017
Contents 1/20
Brain Computer Interface (BCI) A direct connection pathway between the brain and external world. BCI acquires brain signal in response to a certain type of behavior and decode it into the device control commands. 2/20
Steady Brain State Computer Visual Interface Evoked Potential (BCI) Response to flickering stimulus. Generates in the visual cortex of the brain. It contains stimulus frequency and its harmonics. 3/20
Brain PSD Computer of SSVEP Interface Signal(BCI) Amplitude spectrum of the SSVEP BCI signal for P7, O1, O2, P8 electrodes in 17Hz stimulus frequency 6/20
Brain Why Computer SSVEP Interface signal? (BCI) SSVEP needs less training time Information transfer rate is high It has higher classification accuracy 4/20
Brain SSVEP Computer based Interface BCI system (BCI) Typical structure of the SSVEP based BCI system 5/20
Brain Computer Visual stimulus Interface (BCI) Visual Stimulus Design Mechanical design MCU and control color and frequency Connection between MCU and PC 7/20
Brain Computer Visual stimulus Interface (BCI) 7/20
Brain Computer Data acquisition Interface (BCI) 14 channels: AF3, F7, F3, FC5, T7, P7, O1, O2, P8, T8, FC6, F4, F8, AF4 References: In the CMS/DRL noise cancellation Sampling rate: 128 SPS Resolution: 14 bits 1 LSB = 0.51μV Bandwidth: 0.2 43Hz Wireless and rechargeable 8/20
Brain Computer Data acquisition Interface (BCI) Distance between the stimulus and subject is 80 [cm]. Visual stimulus frequencies are 11, 13, 15 and 17 [Hz]. The color of the stimulus is set to green. Electrodes placed on O1, O2, P7 and P8 locations. 9/20
Brain Computer Data Processing Interface (BCI) Likelihood Ratio Test (LRT) method M = mean value C = Covariance matrix The reference signal 10/20
Brain Computer Data Processing Interface (BCI) Likelihood ratio for static signal The measure of association L=1: data are perfectly correlated L=0: data are uncorrelated 11/20
Brain Virtual Computer robotic Interface arm (BCI) Virtual model of RV2AJ robot in Solidwork RV2AJ Robot dimensions [mm] 12/20
Brain Virtual Computer robotic Interface arm (BCI) The robot has two degree of freedom. Theta1 and Theta2 are inputs to determine the robot movement. RV2AJ Simulink model 13/20
Brain Computer Interface (BCI) Simulink block diagram of SSVEP based BCI and their connection 14/20
Brain Computer State of the Interface robot (BCI) State of the robot corresponding to stimulus frequency 15/20
Brain Computer Offline Interface (BCI) Data was recorded in ARAS lab Four subject participated in experiments Length of the data is 20 second in four different trails The experiment was performed in dim room 16/20
Brain Computer Offline Interface (BCI) Each time window for processing is four second Accuracy is the number of the correct segments to the total number of segments 16/20
Brain Computer Online Interface (BCI) Online result of LRT algorithm and Classification output in test1 17/20
Brain Computer Online Interface (BCI) Online result of LRT algorithm and Classification output in test2 18/20
Brain Computer Interface (BCI) An effective strategy is done for implementation of complete BCI system. LRT method is evaluated in offline analysis and implemented for online detection. It is improved that the online detection with high accuracy in short time windows are possible. It is improved that the input stimulus frequencies are perfectly distinguishable. The experiments show promising features of the developed system for further application. 19/20